The data used to estimate gravity models of hospital choice typically contain many zeroes (because patients from some locations do not attend a given hospital in some years). Maximum likelihood estimation of discrete choice models gives more robust estimates of the model parameters than linearized models that require ad hoc adjustments to these zero observations.